利用建筑信息模型和区块链的电网基础设施投资进度自动监测和预警方法

IET Blockchain Pub Date : 2024-01-17 DOI:10.1049/blc2.12061
Jing Lu, Weidong Yu, Shihong Wu
{"title":"利用建筑信息模型和区块链的电网基础设施投资进度自动监测和预警方法","authors":"Jing Lu, Weidong Yu, Shihong Wu","doi":"10.1049/blc2.12061","DOIUrl":null,"url":null,"abstract":"In order to improve the precise control level of power grid infrastructure investment, this paper proposes a monitoring and early warning method of power grid infrastructure investment progress based on building information model and blockchain. By capturing the project construction progress images, the features of the power grid infrastructure are extracted automatically. Combined with the technical characteristics of distributed, tamper‐proof, and traceable blockchain, statistical indicators are generated automatically, monitoring and early warning of the investment progress execution deviation are triggered by the rules running on the smart contracts. The case study results show that the mean absolute error of the target image recognition method based on the image features is 4.32%, and the prediction accuracy of the incoming line is better than that of the engineering civil and substation. The early warning model of investment statistics based on smart contracts can automatically monitor the investment progress and generate early warnings, which provides a basis for the dynamic adjustment of the investment plan, and effectively improves the refined management level of power grid infrastructure investment projects.","PeriodicalId":100650,"journal":{"name":"IET Blockchain","volume":" 1094","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Automatic monitoring and early warning method for power grid infrastructure investment progress using building information model and blockchain\",\"authors\":\"Jing Lu, Weidong Yu, Shihong Wu\",\"doi\":\"10.1049/blc2.12061\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to improve the precise control level of power grid infrastructure investment, this paper proposes a monitoring and early warning method of power grid infrastructure investment progress based on building information model and blockchain. By capturing the project construction progress images, the features of the power grid infrastructure are extracted automatically. Combined with the technical characteristics of distributed, tamper‐proof, and traceable blockchain, statistical indicators are generated automatically, monitoring and early warning of the investment progress execution deviation are triggered by the rules running on the smart contracts. The case study results show that the mean absolute error of the target image recognition method based on the image features is 4.32%, and the prediction accuracy of the incoming line is better than that of the engineering civil and substation. The early warning model of investment statistics based on smart contracts can automatically monitor the investment progress and generate early warnings, which provides a basis for the dynamic adjustment of the investment plan, and effectively improves the refined management level of power grid infrastructure investment projects.\",\"PeriodicalId\":100650,\"journal\":{\"name\":\"IET Blockchain\",\"volume\":\" 1094\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IET Blockchain\",\"FirstCategoryId\":\"0\",\"ListUrlMain\":\"https://doi.org/10.1049/blc2.12061\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Blockchain","FirstCategoryId":"0","ListUrlMain":"https://doi.org/10.1049/blc2.12061","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

为了提高电网基建投资的精准管控水平,本文提出了一种基于建筑信息模型和区块链的电网基建投资进度监测预警方法。通过抓取项目建设进度图像,自动提取电网基建特征。结合区块链分布式、防篡改、可追溯的技术特点,自动生成统计指标,通过智能合约上运行的规则触发对投资进度执行偏差的监测和预警。案例研究结果表明,基于图像特征的目标图像识别方法的平均绝对误差为4.32%,进线预测精度优于工程土建和变电站。基于智能合约的投资统计预警模型能够自动监测投资进度并生成预警,为投资计划的动态调整提供依据,有效提高了电网基建投资项目的精细化管理水平。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Automatic monitoring and early warning method for power grid infrastructure investment progress using building information model and blockchain
In order to improve the precise control level of power grid infrastructure investment, this paper proposes a monitoring and early warning method of power grid infrastructure investment progress based on building information model and blockchain. By capturing the project construction progress images, the features of the power grid infrastructure are extracted automatically. Combined with the technical characteristics of distributed, tamper‐proof, and traceable blockchain, statistical indicators are generated automatically, monitoring and early warning of the investment progress execution deviation are triggered by the rules running on the smart contracts. The case study results show that the mean absolute error of the target image recognition method based on the image features is 4.32%, and the prediction accuracy of the incoming line is better than that of the engineering civil and substation. The early warning model of investment statistics based on smart contracts can automatically monitor the investment progress and generate early warnings, which provides a basis for the dynamic adjustment of the investment plan, and effectively improves the refined management level of power grid infrastructure investment projects.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
1.80
自引率
0.00%
发文量
0
期刊最新文献
Blockchain transaction data mining and its applications Research on airport baggage anomaly retention detection technology based on machine vision, edge computing, and blockchain Data‐sharing strategies in medical consortium based on master‐slave multichain and federated learning RON‐based cross‐chain routing optimization strategy in metaverse Leveraging ontochains for distributed public transit ticketing: An investigation with the system for ticketing ubiquity with blockchains
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1